Working paper - Why is there so little impact of system dynamics in the most important social questions?

Jay Forrester, in his 2007 paper on System dynamics—the next fifty years, asked a question that has not yet been answered: “Why is there so little impact of system dynamics in the most important social questions?” We have long been working on that question and wish to offer a working paper on the subject for discussion and feedback, as this question is near and dear to the hearts of those who have long been in the system dynamics community.

The paper title is: The process must fit the problem: Integrating root cause analysis with the system dynamics modeling process for difficult problems.

Abstract - System dynamics has the theoretical potential to productively model any dynamic problem where entity flow can be aggregated without significant loss of information and to offer practical solution strategies based on the model. However, in practice, as Jay Forrester observed, the field is presently stagnated “on a rather aimless plateau… there is very little penetration into the big issues.” We argue the central reason is that for the more difficult problems, the present modeling process does not fit the problem because it lacks root cause analysis. This too often results in models that omit a problem’s root causes and therefore the correct high leverage points. The paper begins the conversation for filling this gap by presenting an educational example of a comprehensive process for integrating root cause analysis into the system dynamics modeling process.

The working paper may be found here. Only the first 8 1/2 pages are drafted. The rest is in detailed outline form. This is exactly the stage at which the young paper can benefit most from insightful comments. The direction of the paper is defined, but not the full argument and content.

We hope this will be a stimulating and productive forum discussion. Thanks to all!

Jack Harich and Montserrat Koloffon Rosas

Jack, the paper link is not working.
Len

Thanks Len, sorry it’s not working. I tested it beforehand and it worked. It’s also working now. I’m using Chrome. This is the URL:
http://www.thwink.org/sustain/publications/papers/index.htm#ProcessMustFit

I notice that in Chrome, it says thwink.org links are not secure. Perhaps your browser is preventing you from visiting such links? Just a guess. I’ve also just tested it in Firefox and it’s working there. Perhaps Bob the web wizard can shed some light on this…

Re: change resistance and social force diagrams

The book below discusses why people have a Soldier Mindset and resist change, use faulty reasoning and don’t seek the truth. The media would have us believe political party or ideology determine what people believe. Soldier Mindset uses “directionally motivated reasoning” to determine what to believe.
A Soldier Mindset will never agree to the 5 Why process, or root cause analysis. You can not prove them wrong. They know what a beaver looks like, and that was what was eating the fish, and you can’t convince them otherwise.

Quote: “Research shows that showing people research doesn’t work.” John Sterman MIT

Recommendation: The Scout Mindset: Why Some People See Things Clearly and Others Don’t
by Julia Galef

Hi Richard,

Thanks for your comment. First, only the roughed in outline spoke of “change resistance and social force diagrams.” The first eight pages did not. Those pages are what we are most looking for comments on.

For your comment to be useful, it would help to explain precisely where in our research it applies and how it applies. “Change resistance and social force diagrams” is too general. I really have no idea what you have in mind. Perhaps you can explain? Can you quote the material it applies to, and provide a reasoned argument for how it applies? We would really appreciate that.

Regarding: “A Soldier Mindset will never agree to the 5 Why process, or root cause analysis. You cannot prove them wrong. They know what a beaver looks like, and that was what was eating the fish, and you can’t convince them otherwise.” - If I understand what you’re trying to say correctly, this doesn’t apply to a process for system dynamics modelers. That is the audience for the paper, not the public at large, some of whom might be soldiers.

Regarding: “Quote: “Research shows that showing people research doesn’t work.” John Sterman MIT” – Can you put that quote in context? The vast majority of the people I know do believe information based on solid research. Perhaps the quote refers to the well-known cognitive psychology behavior of confirmation bias? If a person already believes something strongly, they tend to accept and seek out information supporting the belief and reject and avoid information refuting the belief.

I did look at the book. Thanks. Cool stuff. Perhaps the author has published a paper demonstrating and/or arguing how this theory applies to human behavior? Otherwise, it doesn’t seem that much different from thousands of other popular psychology books for personal growth or helping others. The blurb saying “The Scout sees more clearly, makes better judgements, and enjoys the freedom and thrill of discovery. Learn how to be a scout” tells me it’s a self-help book.

“First, only the roughed in outline spoke of “change resistance and social force diagrams.” The first eight pages did not. Those pages are what we are most looking for comments on.”

OK, I guess I was wrong about the book’s concepts applying to your topic. Galef suggested in her book that the concepts are scalable and could be applied at a larger scale, so was wondering if maybe you might be able to apply them to your project. Guess not.
Take Care
Richard

Ah, I see, thanks. Did Galef show specifically how the concept could be scaled, or offer any clues? Or was it just speculation? Our work deals with systemic change resistance, rather than individual change resistance or behavioral factors.

When I built an SD model of climate change I showed that increasing CO2 in the atmosphere was the root cause, along with other greenhouse gases. That SD model was based on the Steffan-Boltzmann equation and many unit conversion values. That SD model was science based using physics equations. Next, one would need to build an SD model of how to control CO2 and other greenhouse gas emissions in order to reduce their concentration in the atmosphere. That would penetrate into a big issue.

An example of not identifying the root cause is how to help low income people. Providing food pantries and free lunches at schools does not result in taking action at the correct high leverage point. Actually, people suffering from food insecurity need free childcare, low cost housing and low cost transportation. Giving people a monthly stipend with no strings attached gives them the opportunity to improve their lives and eventually support themselves using a high leverage point. This was done in Stockton CA.

As you state, "society’s largest problems are of such scale and public interest that they must be addressed by governments.” Is government the system that lacks a root cause analysis? Does this result in omitting a problem’s root causes and therefore the correct high leverage point in the government system?

As you state, “Industry’s solution to its top wicked problem was continuous improvement…”. Government’s solution to its top wicked problems is continuous improvement of all kinds but the time frame of implementing improvements might be decades or centuries. The US government still uses the electoral college defined in the Constitution and as modified by the 12th amendment, adopted in 1804, that solidified the two political parties.

The history of RCA on pages 3 and 4 is irrelevant to the main question of your paper.

The message of this paper on page 5 in italics uses an “If-Then” format. An SD model or SD modeler that uses “If-Then” statements pre-determines the result. You are forcing a specific outcome without any RCA or allowing the dynamic system to show you the high leverage points. You are writing a paper about RCA and dictating to SD modelers that they must use RCA or they are going to omit the correct high leverage points.

My point: A better use of your time would be to take action and apply the process you are advocating, to one or more government systems that are trying to solve wicked problems.

On page 5, doctors use a process of elimination to diagnose and treat patient illness. Once they’ve eliminated potential problems then they focus on what’s left. That’s how they narrow in on the root cause. Again, on page 8, problem 1, doctors also triage a patient and treat immediate problems first, then get more tests and narrow in on the root cause.

One assumption you might be making is that SD models are the real world in the same way that Industry used RCA to change the real world. However, SD models are not the real world. SD models never include the root cause. SD models give you insights into why systems cause people to behave the way they do. Systems determine why people behave the way they do.

Conclusion

Instead of writing a paper about the process, apply your process to a real world wicked problems like climate change, pandemic, voting rights, system racism and many other social issues. Show me, don’t tell me.

Hi
About the ‘aimless plateau’, Jay forester gave his own explanation: the general mediocre and superficial quality of the profession models. He advised too anybody really interested to cut all links to official or public organisations and to work on his own. This was reported by Jack Homer some years before.
Of course, the explanation of the poor SD impact on the real world depends on its author.
From my point of view the explanation does not come from root causes. Finding root causes will generate huge models with infinite boundaries and will lead to the big bang, 13 billions years earlier.
It comes from the lack of knowledge and experience of how the real world is functioning by the modelers who may be good in maths but have rarely worked within it. This lack of experience generates first bad and uncredible models but more importantly suspicion from the decision takers.
When I look at the models presented at an SD conference, they all look uncredible, proposing policies that should be applied but not that could be applied.
Regards.
JJ

Hi Richard,

Thanks for the helpful feedback. Let me address some of your points:

“When I built an SD model of climate change, I showed that increasing CO2 in the atmosphere was the root cause, along with other greenhouse gases.” – The paper said “A root cause is the deepest cause in a causal chain (or the most basic cause in a feedback loop structure) that can be resolved.” You don’t seem to be using that definition. Tracing the causal chain of CO2 emissions, we find many deeper causes, like vehicle emissions, that have even deeper causes, like long commutes and drivers not taking public transport. The rising level of CO2 in the atmosphere is an intermediate cause.

“An example of not identifying the root cause is how to help low income people.” – The note in the paper said “Can anyone think of an actual case where a completed SD model was later discovered to not include the root cause(s)?” Are you describing a completed SD model was later discovered to not include the root cause(s)? Where exactly is this model?

“As you state, ‘society’s largest problems are of such scale and public interest that they must be addressed by governments.’ Is government the system that lacks a root cause analysis? Does this result in omitting a problem’s root causes and therefore the correct high leverage point in the government system?” – Nice question, but what does “Is government the system that lacks a root cause analysis?” mean? Are governments not using RCA or is RCA not being performed on why governments are unable to address this problem?

“As you state, ‘Industry’s solution to its top wicked problem was continuous improvement…’. Government’s solution to its top wicked problems is continuous improvement of all kinds but the time frame of implementing improvements might be decades or centuries. The US government still uses the electoral college defined in the Constitution and as modified by the 12th amendment, adopted in 1804, that solidified the two political parties.” – How is this relevant to the paper? What is your specific suggestion to improve the paper or what is the problem in the paper?

“The history of RCA on pages 3 and 4 is irrelevant to the main question of your paper.” – Thanks. If you are familiar with papers, you will realize that most have a literature review of some kind after the introduction, in order to educate the reader on the context of problem and where the paper’s research question and potential contribution fit into the literature. A paper on how to integrate RCA with SD modeling must therefore review RCA. What is it, what does it accomplish, how successful has this method been?

“The message of this paper on page 5 in italics uses an ‘If-Then’ format. An SD model or SD modeler that uses ‘If-Then’ statements pre-determines the result. You are forcing a specific outcome without any RCA or allowing the dynamic system to show you the high leverage points.” – I don’t understand what you are trying to say.

“You are writing a paper about RCA and dictating to SD modelers that they must use RCA or they are going to omit the correct high leverage points.” – Well, I don’t think the paper is “dictating” anything. However, it does present these premises: all causal problems arise from their root causes, difficult modeling problems are causal problems, and RCA is the only known method of reliably and efficiently finding and resolving root causes. Therefore, if a problem is so difficult that non-RCA-based methods are failing, then it would be prudent for the problem solver to use RCA. This is exactly why RCA is the foundational method for all large-scale industrial processes. The paper attempts to allow SD modelers to be just as successful. RCA is not perfect. People (especially those in training) do miss root causes on their first pass, so they try again. But RCA is orders of magnitude better than non-RCA methods like trial and error, expert judgement, statistical correlation, and so on, for difficult causal problems.

“My point: A better use of your time would be to take action and apply the process you are advocating, to one or more government systems that are trying to solve wicked problems.” – Thanks, but this makes little sense. Method papers are common, especially in the social sciences. Editors and readers are not rejecting them for the reason you use, because papers about potential new methods, or method changes, are extremely useful. Sometimes data precedes theory, and sometime theory precedes data. That’s the way scientific progress works.

“On page 5, doctors use a process of elimination to diagnose and treat patient illness. Once they’ve eliminated potential problems then they focus on what’s left. That’s how they narrow in on the root cause.” – This seems to argue that doctors are not using RCA but are using something else. You seem to be very resistant to the idea that RCA can be useful. RCA is the foundational method behind all formal methods of solving causal problems. The paper says “RCA is the systematic practice of finding, resolving, and preventing recurrence of the root causes of causal problems.” How does the process of elimination (a systematic practice) to find the root cause of an illness not fit this definition?

“Again, on page 8, problem 1, doctors also triage a patient and treat immediate problems first, then get more tests and narrow in on the root cause.” – Triage has nothing to do with RCA. It’s a problem management issue.

“One assumption you might be making is that SD models are the real world in the same way that Industry used RCA to change the real world.” – I don’t understand. Perhaps you are writing too fast?

“However, SD models are not the real world. SD models never include the root cause.” Models frequently contain root causes, in the same sense that models contain things like growth rates and population. A successful policy resolves the root causes and solves the problem, first in the model, and then the real world. Many SD models have done this, as it is usually their primary purpose. Of course, they usually don’t use root cause terminology.

“Conclusion. Instead of writing a paper about the process, apply your process to a real world wicked problems like climate change, pandemic, voting rights, system racism and many other social issues. Show me, don’t tell me.” – This repeats an earlier comment you made, starting with “My point.” See my reply to that.

Richard, I hope my replies help you to see a little deeper into the complex situation the paper attempts to deal with. It wasn’t easy to write.

Thanks again,

Jack Harich

Hi JJ,

I appreciate your taking the time to look the paper over and share your feedback. My comments are below.

“About the ‘aimless plateau’, Jay forester gave his own explanation: the general mediocre and superficial quality of the profession models. He advised to anybody really interested to cut all links to official or public organizations and to work on his own. This was reported by Jack Homer some years before.” – Thanks. Why is the quality of SD models on difficult problems low? The paper argues it’s because modeling is not RCA driven.

“Of course, the explanation of the poor SD impact on the real world depends on its author. From my point of view the explanation does not come from root causes. Finding root causes will generate huge models with infinite boundaries and will lead to the big bang, 13 billion years earlier.” – You seem to be saying that RCA cannot help SD modelers solve problems, because that will generate huge unmanageable models. Why will this happen? You imply it’s because asking why successively will have no end. Let me explain why that’s not true.

The paper says “A root cause is the deepest cause in a causal chain (or the most basic cause in a feedback loop structure) that can be resolved.” The Five Whys example goes five layers deep to find the root cause. An SD model of the “Why did the machine stop” problem would be small or medium size. There would be no tendency to be infinitely large. Does this help you to see that RCA can be applied practically?

“It [the explanation of the poor SD impact on the real world] comes from the lack of knowledge and experience of how the real world is functioning by the modelers who may be good in math but have rarely worked within it. This lack of experience generates first bad and uncredible models but more importantly suspicion from the decision takers.” – I think you are saying that low modeler expertise in a problem area causes low quality models. The SD literature disagrees. It says that by following best practices, high quality models can be produced. Acquiring a high level of modelling expertise takes time and training. The record shows that many times modelers who were not already familiar with a problem have been able to apply best practices and produce good models that solved problems or allowed significant progress in the client’s eyes. Please see Sterman’s book, Jack Homer’s book, and many SDR articles for proof.

Thanks,

Jack Harich

You might consider the possibility of reading The Scout Mindset and practicing some of the actions suggested by the author. Like all of us, including myself, we tend to default to the Soldier Mindset.
Thanks
Richard

Hi Jack
Thank you for your answer. Technically I agree with you but mixing my experience in the real world will generate different conclusions. To agree with you globally would need that we share quite similar life experiences: I have been managing an SME (100 employees) for 40 years and been in the board of another family business (about 80 employees) for about the same time plus other experiences: a franchising system, a common central buying system for French vehicles renters, a consultancy in mathematical finance, a cinema production company. I have too a good mathematical background and more than 40 years of programming experience (building my own business information system) and 20 years of SD practice. The mixing of all these experiences generated conclusions that are impossible to explain, especially to people with different experiences. I have experimented this in past SD forums. The only solution is for each party to progress on its own and this is what I am doing and I wish that you will do it too.
I looked too at the common property laws, an interesting idea. But its implementation will be difficult because common property means no unique owner. Common goods are the property of everybody and nobody at the same time, generating a low level of motivation. This is why private management will always be more performant than public one.
Regards.
JJ